Workshop on Knowledge Graphs (KnowGraphs)
colocated to COLLABORATECOM 2019
August 19-22, 2019
London, Great Britain
Motivated by the ambition of omnipresent AI coverage in life, a current trend of distributed computing of IoT devices is extending as a Fog Computing landscape from centralized Cloud Computing to Edge Computing to facilitate the networked electronics, software, sensors, Internet of Things (IoT) to collect and exchange content. This extension has empowered huge amount of IoT devices with enhanced capabilities of functionalities through extended integration, connection and communication among originally separated IoT devices. Alongside the increasing of the amount of accumulated content is the increased demand of effort to be put into processing corresponding content for various purposes including privacy protection and sharing of content resources. The accumulation of content resources from multiple sources means more than the increase of the amount of content alone. The more sources the content are integrated, the more likely the types of the content sources are diversified into. Since usually for each type of content a usage solution needs to be designated for it, more types of content will demand more solutions for them.
Another increasingly true demand on processing load of the extension from Cloud to Edge is that more types of resources than raw data will be cooperatively or autonomic processed through incorporating the nodes both at the Edge and at the Cloud. The types of resources to be processed will cover all types of DIKW pyramid including data, information, knowledge and wisdom (DIKW) hopefully. Therefore the operations will cover data sensing and acquisition, information analysis and abstraction, knowledge generation and reasoning, etc, especially in the form of various promising graph based solutions not limited to Knowledge Graphs.
Thereafter, the enhanced capability from the accumulation of otherwise discrete processing and storage as a flexible whole also brought various new challenges on graph based solutions: (a) new methodologies on conceptual modeling of the typed resources of data, information and knowledge at the source of IoT as typed content, (b) how to extend existing graph based solutions to model the demand of the increase of the computation, storage, and communication complexity corresponding to the increase of the amount of to be processed content for existing functionalities, (c) how to design graph based functionalities to process new types or new mixed types of content brought by various integrated devices, and (d) how to ensure and validate the graph based solutions meet the demand on both the time and energy efficiency and effectiveness of dealing with both increase of the amount of the target content and the types of the content of the collaborated IoT devices.
In this workshop, we will invite papers that present new theories, methods and techniques applied to value or quality driven resource processing in IoT and Edge Computing. We particularly encourage papers demonstrating novel strategies to according the types of to be processed content. Applications may be drawn by investigating the usage of novel graph based methods for all aspects of resource processing, including system design, performance optimization, algorithm design, scheduling methods, energy saving, and security management. Specific topics may include the following areas:
List of topics
- Graph based data acquisition and linking for IoT and Edge Computing
- Graph based dynamic information modeling for IoT and Edge Computing
- Graph based knowledge representation for IoT and Edge Computing
- Graph based information analysis and abstraction for IoT and Edge Computing
- Graph based knowledge creation and reasoning for IoT and Edge Computing
- Graph based DIKW service provision and quality evaluation
- Graph based application of DIKW resources transformation, transfer and storage
- Graph based energy efficiency in Edge Computing
- Value driven optimization of Graph based resources processing
- Formal Modeling and Verification for Graph based resources processing
- Big data and data analysis for Graph based processing
- Security and privacy in Graph based models of DIKW resources
Workshop papers will published together with COLLABORATECOM proceedings.
All registered papers will be submitted for publication by Springer and made available through SpringerLink Digital Library.
CollaborateCom proceedings are indexed in leading indexing services, including Ei Compendex, ISI Web of Science, Scopus, CrossRef, Google Scholar, DBLP, as well as EAI’s own EU Digital Library (EUDL).
Authors of selected papers will be invited to submit an extended version to:
- Mobile Networks and Applications (MONET) Journal (IF: 2.497)
- International Journal of Intelligent Internet of Things Computing
- IEEE ACCESS
- International Journal of Engineering Business Management
- Journal of Organizational and End User Computing (JOEUC)
All accepted authors are eligible to submit an extended version in a fast track of:
Submit your paper here.
Dr. Yucong Duan, Professor, PhD, Hainan University, China
Dr. Kuang Li, Professor, PhD, Central South University, China